Patents Assigned to Resurgo, LLC
  • Machine Learning Model Evaluation in Cyber Defense
    Publication number: 20200364620
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: July 23, 2020
    Publication date: November 19, 2020
    Applicant: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Machine Learning Model Evaluation
    Publication number: 20200356904
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: July 31, 2020
    Publication date: November 12, 2020
    Applicant: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Machine learning model evaluation in cyber defense
    Patent number: 10733530
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Grant
    Filed: December 8, 2016
    Date of Patent: August 4, 2020
    Assignee: RESURGO, LLC
    Inventors: Eamon Hirata Jordan, Chad Kumao Takahashi, Ryan Susumu Ito
  • Machine Learning Model Evaluation in Cyber Defense
    Publication number: 20180165597
    Abstract: Testing machine learning sensors by adding obfuscated training data to test data, and performing real time model fit analysis on live network traffic to determine whether to retrain.
    Type: Application
    Filed: December 8, 2016
    Publication date: June 14, 2018
    Applicant: RESURGO, LLC
    Inventors: EAMON HIRATA JORDAN, CHAD KUMAO TAKAHASHI, RYAN SUSUMU ITO, MATTHEW DAVID-KRISTOFER TROGLIA
  • HETEROGENEOUS SENSORS FOR NETWORK DEFENSE
    Publication number: 20150052609
    Abstract: Heterogeneous sensors simultaneously inspect network traffic for attacks. A signature-based sensor detects known attacks but has a blind spot, and a machine-learning based sensor that has been trained to detect attacks in the blind spot detects attacks that fail to conform to normal network traffic. False positive rates of the machine-learning based sensor are reduced by iterative testing using statistical techniques.
    Type: Application
    Filed: November 3, 2014
    Publication date: February 19, 2015
    Applicant: RESURGO, LLC
    Inventors: Eamon Hirata Jordan, Kevin Barry Jordan, Evan Joseph Kelly
  • Heterogeneous sensors for network defense
    Patent number: 8887285
    Abstract: Heterogeneous sensors simultaneously inspect network traffic for attacks. A signature-based sensor detects known attacks but has a blind spot, and a machine-learning based sensor that has been trained to detect attacks in the blind spot detects attacks that fail to conform to normal network traffic. False positive rates of the machine-learning based sensor are reduced by iterative testing using statistical techniques.
    Type: Grant
    Filed: March 14, 2013
    Date of Patent: November 11, 2014
    Assignee: Resurgo, LLC
    Inventors: Eamon Hirata Jordan, Evan Joseph Kelly, Kevin Barry Jordan